There is a phenomenon in which movement of a crowd that is an assemblage of many people may concentrate in a particular area and a particular time zone, when an event and the like are held. Such a phenomenon includes, for example, movement to a stadium when a sports match is held, movement to a site when a festival such as a fireworks show is held, and the like. Such movement of a crowd requires guidance in consideration of rapidness of movement and safety.
A density of people is an index considered important as safety of a crowd (see NPL 1). The higher a density of people is, the more each person experiences discomfort due to compression. In addition, there is also a reported case in which a much higher density of people may lead to death in worst cases due to difficulty in breathing and unconsciousness. In addition, when a density of people becomes high, falling of a certain person may cause falling of a subsequent crowd, which is also likely to cause an accident such as falling like dominoes.
PTL 1 describes one example of a technique that is related to such a problem in movement of a crowd. The related technique described in PTL 1 assists in drafting a guarding plan by predicting turnout of people in a surrounding spot of an event site and a target guard area. Specifically, this related technique measures flow of people in a surrounding spot relevant to turnout of people, by performing image processing on a video that is obtained from a camera disposed in the surrounding spot. Then, this related technique predicts, based on inflow and outflow data on expected turnout of people in an inflow and outflow spot such as a transportation facility relevant to turnout of people, and an actual measured value of the flow of people measured in the surrounding spot, flow of people in a subsequent surrounding spot and turnout of people in a target guard area.
In addition, PTL 2 describes another example of a technique that is related to the problem in movement of a crowd. The related technique described in PTL 2 determines a congestion degree of a space by detecting a human body with an infrared sensor, and displays the congestion degree on a display device and the like. Specifically, this related technique calculates, as a congestion degree, a rate (an area ratio and the like) of a human-body-existing area detected in a target space. For example, this related technique determines a congestion degree in a train, and notifies in advance a passenger of the congestion degree by displaying the congestion degree on a display device on a vehicle side face.
In addition, PTL 3 describes another example of a technique that is related to the problem in movement of a crowd. The related technique described in PTL 3 provides, to a portable information terminal possessed by a guard deployed in each spot, a means of counting and summing up the number of people getting off at a nearby station of an event site, and accessing, in real time, data on the number of getting-off people obtained by the sum up.
In addition, PTL 4 describes another example of a technique that is related to the problem in movement of a crowd. The related technique described in PTL 4 presents a menu screen to a terminal possessed by a visitor to an exhibition hall, in display priority depending on a congestion degree of each exhibition booth. Specifically, this related technique counts the number of accesses from terminals possessed by visitors to a menu representing each exhibition booth, and lowers the display priority of a menu with a large number of accesses.
In addition, PTL 5 describes another example of a technique that is related to the problem in movement of a crowd. The related technique described in PTL 5 determines a method of guiding to a plurality of evacuation routes, in evacuation guidance from a facility to an evacuation place. Specifically, this related technique predicts, based on an arrival pattern of a user to a facility and a dwell time distribution database, a congestion degree and a congestion peak amount of the facility. Then, this related technique predicts, by distributing the congestion peak amount of the facility to respective evacuation routes in accordance with a set guidance method, a congestion degree and a congestion peak amount of each of the evacuation routes. Then, this related technique determines, by predicting the congestion degree and the congestion peak amount of each of the evacuation routes while varying a guidance method, a guidance method that minimizes the congestion peak amount of each of the evacuation routes.
In addition, PTL 6 describes another example of a technique that is related to the problem in movement of a crowd. The related technique described in PTL 6 presents a path that minimizes cost for passing through a series of destinations, based on a congestion degree of each of different locations in a shopping center, a movement speed and a movement direction of a shopper, a length of a queue, and the like. Specifically, this related technique calculates, from video data, a congestion degree of each of a plurality of spots as destinations of a user, a movement speed and a movement direction, a length of a queue, and the like. Then, this related technique calculates and presents, by using information obtained from the video data, a path that further lowers cost based on time, a distance, and the like while taking in consideration a delay and the like due to congestion.